tj<ddlZddlmZddlmZmZmZmZddlm Z ddl m Z ddl m Z GddeZGd d e ZdS) N)Enum)AnyDictListOptional)CallbackManagerForRetrieverRun)Document) BaseRetrieverceZdZdZdZdZdS) SearchDepthzSearch depth as enumerator.basicadvancedN)__name__ __module__ __qualname____doc__BASICADVANCEDn/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/retrievers/tavily_search_api.pyr r s%% EHHHrr ceZdZUdZdZeed<dZeed<dZ eed<dZ eed<e j Z e ed<d Zeeeed <d Zeeeed <iZeeeefed <d Zeeed <dededeefdZd S)TavilySearchAPIRetrieverafTavily Search API retriever. Setup: Install ``langchain-community`` and set environment variable ``TAVILY_API_KEY``. .. code-block:: bash pip install -U langchain-community export TAVILY_API_KEY="your-api-key" Key init args: k: int Number of results to include. include_generated_answer: bool Include a generated answer with results include_raw_content: bool Include raw content with results. include_images: bool Return images in addition to text. Instantiate: .. code-block:: python from langchain_community.retrievers import TavilySearchAPIRetriever retriever = TavilySearchAPIRetriever(k=3) Usage: .. code-block:: python query = "what year was breath of the wild released?" retriever.invoke(query) Use within a chain: .. code-block:: python from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate from langchain_core.runnables import RunnablePassthrough from langchain_openai import ChatOpenAI prompt = ChatPromptTemplate.from_template( """Answer the question based only on the context provided. Context: {context} Question: {question}""" ) llm = ChatOpenAI(model="gpt-3.5-turbo-0125") def format_docs(docs): return " ".join(doc.page_content for doc in docs) chain = ( {"context": retriever | format_docs, "question": RunnablePassthrough()} | prompt | llm | StrOutputParser() ) chain.invoke("how many units did bretch of the wild sell in 2020") kFinclude_generated_answerinclude_raw_contentinclude_images search_depthNinclude_domainsexclude_domainskwargsapi_keyquery run_managerreturnc " ddlm}n#t$r ddlm}YnwxYwn#t$rtdwxYw|jpt jd}jsjn jdz }|j d||j j jj j jjdjpifd d D}jr+t%d d d ddg|}|S)Nr) TavilyClient)ClientzTTavily python package not found. Please install it with `pip install tavily-python`.TAVILY_API_KEY)r#)r$ max_resultsrinclude_answerr r!rrc Vg|]}tjs|ddn|dpd|dd|dddd|DddiS) content raw_contenttitleurlr2sourcec"i|] \}}|dv || S))r/r2r3r1r).0rvs r zOTavilySearchAPIRetriever._get_relevant_documents...s4 Aq$NNN1NNNrimages page_contentmetadata)r rgetitems)r7resultresponseselfs r zDTavilySearchAPIRetriever._get_relevant_documents..zs    /7VZZ 2666jj//52#ZZ44$jj33  $*LLNN hll844         rresultsanswerr0zSuggested Answerzhttps://tavily.com/r4r;r)tavilyr( ImportErrorr)r#osenvironrrsearchrvaluer r!rrr"r>r )rBr$r%r(rFr,docsrAs` @r_get_relevant_documentsz0TavilySearchAPIRetriever._get_relevant_documents^s  ://///// : : :99999999 :   F   dl&RbjAQ6RSSS$($AQdfftvPQz  6=  #*08 0 0 $ 8.   { b        #,,y11!   $  ( !)h!;!;!3"7  D s ###=)rrrrrint__annotations__rboolrrr rrr rrstrr!r"rrr#rr rMrrrrrs @@DAsKKK%*d*** %%%% ND   + 1L+111+/OXd3i(///+/OXd3i(///')FHT#s(^ $)))!GXc]!!!::*H: h::::::rr)rHenumrtypingrrrrlangchain_core.callbacksrlangchain_core.documentsr langchain_core.retrieversr r rrrrrWs ,,,,,,,,,,,,CCCCCC------333333$GGGGG}GGGGGr